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Statistical atlases and computationa...

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Statistical atlases and computational models of the heartatrial segmentation and LV quantification challenges : 9th International Workshop, STACOM 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : revised selected papers /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical atlases and computational models of the heartedited by Mihaela Pop ... [et al.].
Reminder of title:	atrial segmentation and LV quantification challenges : 9th International Workshop, STACOM 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : revised selected papers /
remainder title:	STACOM 2018
other author:	Pop, Mihaela.
corporate name:
Published:	Cham :Springer International Publishing :2019.
Description:	xiv, 487 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	HeartCongresses.Imaging
Online resource:	https://doi.org/10.1007/978-3-030-12029-0
ISBN:	9783030120290$q(electronic bk.)

Statistical atlases and computational models of the heartatrial segmentation and LV quantification challenges : 9th International Workshop, STACOM 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : revised selected papers /
Statistical atlases and computational models of the heartatrial segmentation and LV quantification challenges : 9th International Workshop, STACOM 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : revised selected papers /[electronic resource] :STACOM 2018edited by Mihaela Pop ... [et al.]. - Cham :Springer International Publishing :2019. - xiv, 487 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,113950302-9743 ;. - Lecture notes in computer science ;4891..

Cardiac imaging and image processing -- Machine learning applied to cardiac imaging and image analysis -- Atlas construction -- Statistical modelling of cardiac function across different patient populations -- Cardiac computational physiology -- Model customization -- Atlas based functional analysis -- Ontological schemata for data and results -- Integrated functional and structural analyses -- Pre-clinical and clinical applicability of these methods.

This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.

ISBN: 9783030120290$q(electronic bk.)

Standard No.: 10.1007/978-3-030-12029-0doiSubjects--Topical Terms:

438630
Heart
--Imaging--Congresses.

LC Class. No.: RC683.5.I42

Dewey Class. No.: 616.120757

Statistical atlases and computational models of the heartatrial segmentation and LV quantification challenges : 9th International Workshop, STACOM 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : revised selected papers /
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520 $a This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.
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